As biomass fuel use in developing countries causes substantial harm to health and the environment, efficient stoves are candidates for subsidies to reduce emissions. In evaluating improved stoves’ relative benefits, little attention has been given to who received which stove intervention due to choices that are made by agencies and households. Using Chinese household data, we find that the owners of more efficient stoves (i.e., clean-fuel and improved-biomass stoves, as compared with traditional-biomass and coal stoves) live in less healthy counties and differ, across and within counties, in terms of household characteristics such as various assets. On net, that caused efficient stoves to look worse for health than they actually are.We control for counties and household characteristics in testing stove impacts. Unlike tests that lack controls, our preferred tests with controls suggest health benefits from clean-fuel versus traditional-biomass stoves. Also, they eliminate surprising estimates of health benefits from coal, found without using controls. Our results show the value, for learning, of tracking who gets which intervention.

BACKGROUND: Many studies associate health risks with household air pollution from biomass fuels and stoves. Evaluations of stove improvements can suffer from bias because they rarely address health-relevant differences between the households who get improvements and those who do not. METHODS: We demonstrate both the potential for bias and an option for improved stove inference by applying to household air pollution a technique used elsewhere in epidemiology, propensity-score matching (PSM), based on a stoves-and-health survey for China (15 counties, 3500 households). RESULTS: Health-relevant factors (age, wealth, kitchen ventilation) do in fact differ considerably between the households with stove improvements and those without. We study the resulting bias in estimates of cleaner-stove impacts using a self-reported Physical Component Summary (PCS). Typical stoves-literature regressions with little control for non-stove factors suggest no benefits from a cleaner-fuel stove relative to a traditional biomass stove. Yet increasing controls raises the impact estimates. Our PSM estimates address the differences in health-relevant factors using ‘apples to apples’ comparisons between those with improved stoves and ‘similar’ households. This generates higher estimates of clean-stove benefits, which are on the order of one half the standard deviation of the PCS outcome. CONCLUSIONS: Our data demonstrate the potential importance of bias in household air pollution studies. This results from failure to address the possibility that those receiving improved stoves are themselves prone to better or worse health outcomes. It suggests the value of data collection and of study design for cookstove interventions and, more generally, for policy interventions within many health outcomes.

We consider health and environmental quality in developing countries, where limited resources constrain behaviors that combat enormously burdensome health challenges. We focus on four huge challenges that are preventable (i.e., are resolved in rich countries). We distinguish them as special cases in a general model of household behavior, which is critical and depends on risk information. Simply informing households may achieve a lot in the simplest challenge (groundwater arsenic); yet, for the three infectious situations discussed (respiratory, diarrhea, and malaria), community coordination and public provision may also be necessary. More generally, social interactions may justify additional policies. For each situation, we discuss the valuation of private spillovers (i.e., externalities) and evaluation of public policies to reduce environmental risks and spillovers. Finally, we reflect on open questions in our model and knowledge gaps in the empirical literature including the challenges of scaling up and climate change.

This paper provides a theoretical explanation for the widely debated empirical finding of “Environmental Kuznets Curves”, i.e., U-shaped relationships between per-capita income and indicators of environmental quality. We present a household-production model in which the degradation of environmental quality is a by-product of household activities. Households can not directly purchase environmental quality, but can reduce degradation by substituting more expensive cleaner inputs to production for less costly dirty inputs. If environmental quality is a normal good, one expects substitution towards the less polluting inputs, so that increases in income will increase the quality of the environment. It is shown that this only holds for middle income households. Poorer households spend all income on dirty inputs. When they buy more, as income rises, the pollution also rises. they do not want to substitute, as this would reduce consumption of non-environmental services for environmental amenities that are already abundant. Thus, as income rises from low to middle levels, a U shape can result. Yet an N shape might eventually result, as richer households spend all income on clean inputs. Further substitution possibilities are exhausted. Thus as income rises again pollution rises and environmental quality falls.

Will economic growth inevitably degrade the environment, throughout development? We present a household-level framework emphasising the trade-off between consumption that causes pollution and pollution-reducing abatement. Our model provides a simple explanation for upward-turning, non-monotonic paths of environmental quality during economic growth. Its innovation yields sufficient conditions that simultaneously address preferences and technologies. With standard preferences, an asymmetric endowment (i.e., at zero income, consumption is also zero but environmental quality is positive) leads low-income households not to abate, and further this condition is sufficient for an environmental Kuznets curve (EKC) for a wide range of abatement technologies. Without such an endowment, however, even strong economies of scale in abatement are, on their own, insufficient for an EKC

Rich-poor interactions complicate the search for a stable Environmental Kuznets Curve (an ‘inverted U’ relationship between income per-capita and environmental degradation). We show that aid from richer to poorer countries to support investments in environment, in either of two forms, alters the income-environment relationships that otherwise exist, lowering levels of degradation in the poorer countries conditional upon their incomes. Yet even with environmental aid, in our model environmental quality eventually falls as economic growth continues, although ongoing innovation could change that conclusion. In light of this result, we show that subsidies to clean goods, one form of technological-transfer aid programme, dominate income transfers as environmental aid policy by the rich. Given that aid matters, we then show that when rich countries degrade the environment, a perverse effect exists: when an aid-giving country becomes richer, it gives less aid to the poor country. This is stronger when that degradation is durable, that is, when consumption and degradation by the rich country in the past has durable effects upon the environment.

The fuel-use decisions of households in developing economies, because they directly influence the level of indoor air quality that these households enjoy (with its attendant health effects), provide a natural arena for empirically assessing latent preferences towards the environment and how these evolve with increases in income. Such an assessment is critical for a better understanding of the likely effects of aggregate economic growth on the environment. Using household data from Pakistan we estimate Engel curves for traditional (dirty) and modern (clean) fuels. Our results provide empirical support for a household production framework in which non-monotonic environmental Engel curves can arise quite naturally. Under plausible assumptions about the emissions implied by fuel use, our estimates yield an inverted-U relationship between indoor air pollution and income, mirroring the environmental Kuznets curves that have been documented using aggregate data. We then demonstrate, through a simple voting model, that this household-choice framework can generate aggregate EKCs even in a multi-agent setting with heterogeneous households and purely external environmental effects.